Compare models
Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.
| Attribute | mai-ds-r1:freeNot in the catalogue | GPT-6.1 Solgpt-6.1-sol | Nemotron 3.5 Super VL (Free)nemotron-3.5-super-vl:free |
|---|---|---|---|
| Pricing | |||
| Input | — | $2.00 / 1M | $0 / 1M |
| Output | — | $10.00 / 1M | $0 / 1M |
| Cache Write (5m) | — | $2.00 / 1M | — |
| Cache Write (1h) | — | $2.00 / 1M | — |
| Cache Read | — | $2.00 / 1M | $0 / 1M |
| Web Search | — | $0 / 1M | — |
| Cache Write | — | — | $0 / 1M |
| Context | |||
| Max context | — | 1M | 1M |
| Max output | — | N/A | N/A |
| Capabilities | |||
| Vision | — | Yes | Yes |
| Function Calling | — | Yes | Yes |
| JSON Mode | — | Yes | Yes |
| Streaming | — | Yes | Yes |
| Catalogue | |||
| Provider | — | OpenAI | NVIDIA |
| Category | — | chat | chat |
| Charge type | — | Pay As You Go | Free |
| Released | — | — | — |
| Description | |||
| Summary | — | GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical. | NVIDIA Nemotron 3.5 Super VL is an open multimodal Mixture-of-Experts (MoE) model featuring 120B total parameters with 12B activated per token. Built on a hybrid Mamba–Transformer architecture with multi-token prediction, it supports text, images, documents, GUI screenshots, and video inputs, along with a 1M-token context window for complex, long-horizon workflows. Optimized for multimodal reasoning, visual understanding, and agentic tool use, the model supports configurable reasoning modes and token budgets. It is well suited for document intelligence, web research, coding validation, customer service, GUI analysis, and video understanding, enabling efficient, long-running multimodal agent applications. |